Young people get frustrated when they help older people with technology. There are considerable sighs, rolling eyes, and the situation often ends in yelling. One frustration young people are forced to deal with is teaching an older person how to use a search engine. Trying to explain how to enter information into the text box, the meaning of keywords, and how to tell the difference between results is not easy. However, search engines like Google, Bing, and Yandex try to make the search process as easy as possible so everyone can become a search expert.

Learning how to search is not the only thing people have trouble learning. Tech Viral wrote about the top “how to” searches in the article, “Here Are The Top 100 ‘How To’ Searches That People Want To Know.”Xaquin GV researched how people use Google as the answer all “how to” tool and discovered the most popular searches. Among the top “how to “searches are how to make money, how to tie a tie, how to draw, how to kiss, how to lose weight, how to make pancakes, and how to get pregnant.

The essay also examines the top 100 ‘How to’ searches conducted worldwide, and the results are very illustrative. Xaquin divided those searches into categories, with visual representations of how popular each of them is.

The search results mostly revolve around activities that are adult responsibilities along with a few surprises that concern current trends. Everyone can become an expert at any activity with a few simple keystrokes and tutorial guides. YouTube makes “how to” guides more helpful and even more dangerous when people try to copy the experts at parkour, skateboarding, and daredevil activities that should never be tried at home kids.

Olson said the firm’s web analysis revealed search interest for Amazon-related words grew 24 percent year over year in the June quarter versus 23 percent growth in the March quarter. He cited how Piper’s search analysis had a 95 percent correlation with Amazon’s retail sales unit growth in the previous 37 quarters.

Such interest may be spurred by Amazon’s purchase of Whole Foods, and by the company’s strong growth in this year’s second quarter. The innovative analyst’s company, Piper Jaffray, has been in business since 1895. It is nice to see a venerable firm embrace a fresh idea, but will Olson’s prediction prove correct?

From the perspective of the digital marketers they are, GeoMarketing ponders, “How Will Visual and Voice Search Evolve?” Writer David Kaplan consulted Bing Ads’ Purna Virji on what to expect going forward. For example, though companies are not yet doing much to monetize visual search, Virji says that could change as AIs continue to improve their image-recognition abilities. She also emphasizes the potential of visual search for product discovery—If, for example, someone can locate and buy a pair of shoes just by snapping a picture of a stranger’s feet, sales should benefit handsomely. Virji had this to say about traditional, voice, and image search functionalities working together:

A prediction that Andrew Ng had made when he was still with Baidu was that that ‘by 2020, 50 percent of all search will be image or voice.’ Typing will likely never go away. But now, we have more options. Just like mobile didn’t kill the desktop, apps didn’t kill the browser, the mix of visual, voice, and text will combine in ways that are natural extensions of user behavior. We’ll use those tools depending on the specific need and situation at the moment. For example, you could ‘show’ Cortana a picture of a dress in a magazine via your phone camera and say ‘Hey Cortana, I’d love to buy a dress like this,’ and she can go find where to buy it online. In this way, you used voice and images to find what you were looking for.

The interview also touches on the impact of visual search on local marketing and how its growing use in social media offers data analysts a wealth of targeted-advertising potential.

In my files, I had a copy of “Duck Duck Go: Illusion of Privacy.” This document comments on the hurdles a public Web search system must jump over in order to deliver privacy. You can find the write up at this link. If you want to test some privacy-oriented search systems, there are some DuckDuckGo.com alternatives. I am not endorsing these outfits; I am passing along some links because within the last couple of years I learned that privacy is part of the marketing for these systems: [a] Ixquick which is now Startpage at www.startpage.com. This is a metasearch engine which means that the user’s query is passed (in theory anonymously to Bing, Google, Yandex, et al). [b] Unbubble.com (Note that this European service asserts “strong privacy.” The link is www.unbubble.eu [c] Gibiru service (www.gibiru.com) emphasizes anonymous search. Gibiru provides a link to the Firefox Anonymox plug in. But the most recent version of Firefox has been tricky for us, however. My personal view on search anonymization is that when I research my books about cyberosint, the Dark Web, and eDiscovery for cyber intelligence, I assume that I have a number of individuals thrilled with the sites we uncover, write up, and describe in our lectures and webinars. In short, I avoid trying to be “tricky” because I can explain the thousands of queries we run about many exciting topics. See www.xenky.com/darkwebnotebook for a sampler.

The United States imprisons more people than any other country in the world. The justice system, however, is broken and needs to be repaired. How can this be done? IBM’s Watson might have the answer. Engadget shares that: “Watson Is Helping Heal America’s Broken Criminal-Sentencing System” and it could be the start of fixing the broken system. One of the worst problems in the US penitentiary is overcrowding and that most of the incarcerated people are in a minority ethnic group.

Watson is being implemented to repair this disparity. Human judgment can be swayed by the smallest item, so implementing artificial intelligence may make the justice system more objective. AI is not infallible is can wrongly sentence convicts. The best solution right now is to use a mixture of AI and real human logic. IBM works hand and hand with Ohio’s Montgomery County Juvenile Court System to start a pilot program that provides a judge a summary of a child’s life in order to make better choices for his/her care.

Judge Anthony Capizzi is eager to use the AI care-management system, because it will help him synthesize information better and hopefully make more informed decisions.

With this system, however, the judge is afforded a more-complete view of the child’s life, her essential information displayed on a dashboard that can be updated in real-time. Should the judge need additional details, he can easily have it pulled up. [Capizzi said], ‘If I have 10 care providers in my region, can Watson tell me — because of where that child lives, their educational background, their limitations, their family — is there a better one for that child versus the nine others?’

The Watson-based system will deliver more accurate answers the more information fed into it. The hope is that it will be implemented in the other Ohio counties and other systems will be developed for other justice systems. There is still the potential that the Ai could become biased, but there is always a learning curve to make the system work and build a better justice system for the future.

Blogger.com may be sitting on the sidelines. An injured thigh muscle maybe? How can a business create a presence in Google results without a Web page?

That’s the question “Local SEO” tries to answer. And answer the question it does.

The write up does a good job of explaining how to create a “free” Web page about your business complete with images.

My thought is that the Google may be enriching its trove of information with free services that foreshadow content creation.

Instead of searching for user-created blog content in Google News via a wonky hidden option, the user created content can just “live” within the Google Local system.

That’s one way to deliver “unified search.” Remember that concept from the universal search assertions from about 10 years ago.

Fragmentation in Google services? What fragmentation? There’s no fragmentation in Android and there is no fragmentation in Google search results as long as one runs separate, serial queries across Google Books, Google News, et al. Oh, and Blogger.com. Perhaps not for long?

I read “Amazon Shakes Up Search, Again.” I was not aware of Amazon’s shaking up search because there are numerous ways to define the term. The write up narrows “search” to people in three countries who buy products or look for product information online. Ah, good, I think.

My hunch is that the “shake up” is related to the data that suggests Amazon has three times as many product searches than Google. The assertion did not “shake” me up because Google’s product search is not particularly useful. I thought that Froogle had a shot at becoming a daughter-of-Amazon, but the GOOG lost interest. Sure, I can search for a product using Google, but the results are often not what I want. Your mileage may vary.

But back to the write up. I noted some factoids which may be useful to those who are giving talks about product search, those who work for a consulting firm and must appear super smart, or folks like me who collect data, no matter how wild or crazy.

Here we go with the “shake up” from 3,100 consumers in the US, Germany, and the UK:

72 percent use Amazon to research a product before buying the product

51 percent use Amazon as a way to get “alternative ideas”

26 percent use Amazon to get information and price when they plan on visiting a real store

84 percent of “searchers” in the US use Google

71 percent of “searchers” in the US use Amazon

36 percent use Facebook in the US use Amazon

24 percent use Pinterest in the US use Amazon

31 percent use eBay in the US use Amazon

80 percent in the UK use Google

73 percent use Amazon in the UK

9 percent use Bing in France

6 percent us Bing in the UK

6 percent use Bing in Germany

20 percent of searchers use Bing

Amazon stocks or “carries” 353 million products. Put aside the idea that percentages usually work on a scale of zero to 100, please:

59 percent are “health and beauty”

57 percent are “music, movies, or games”

55 percent are “books”

52 percent fashion or clothing

46 percent are home appliances

40 percent are furniture and home furnishings

39 percent are toys

34 percent are sports equipment and clothing

26 percent are garden equipment and furniture (?)

26 percent are food and grocery

9 percent are beer, wine and spirits.

So if there are 353 million products and the percentage data are correct, the total percentage of products is 443 percent. I did not the duplicate furniture entry but counted the percentage anyway. Also, there was no value for garden equipment and furniture so I used “26 percent”. Close enough for millennials steeped in new math.

My math teacher (Verna Blackburn) in my freshman year of high school in 1958 had an dunce cap. I think I can suggest one research report author who might have been invited to wear the 24 inch tall cap. The 443 percent would shake up deal Miss Blackburn. She also threw chalk at students when they made errors when solving on the blackboards which were on three walls of her classroom. The fourth wall looked out over asphalt to the smokestacks of the former RG Letourneau mortar factory. Getting math wrong at that outfit could indeed shake up some things.

Most Google users never think about bias and politics when they search or read suggested pages. Many, though, believe that the average Google user is being sold a bill of goods when searching about climate on Google. A recent WUWT investigation discovered that Google is manipulating the search results to favor left-leaning political ideas. WUWT quotes Google as claiming that their ranking is determined by the following criteria: “High-quality information pages on scientific topics should represent a well established scientific consensus on issues where such consensus exists.” (Section 3.2)

The author goes on to explain,

But the allegations of ‘scientific consensus’ are made only in one field – climate alarmism! ‘Scientific consensus’ is almost an oxymoron. The consensus is a decision-making method used outside of science.

Google was set up to be free from bias, but according to their own explanation, they tend to support the most popular opinion which is a dangerous route to take. Would people want a truly impartial system of search, allowing each searcher to evaluate the source for accuracy and ‘scientific consensus’, or do we like to rely on others, and Google, to make the hard decisions for us?

I read a write up called “Semantic, Adaptive Search – Now that’s a Mouthful.” I cannot decide if the essay is intended to be humorous, plaintive, or factual. The main idea in the headline is that there is a type of search called “semantic” and “adaptive.” I think I know about the semantic notion. We just completed a six month analysis of syntactic and semantic technology for one of my few remaining clients. (I am semi retired as you may know, but tilting at the semantic and syntactic windmills is great fun.)

The semantic notion has inspired such experts as David Amerland, an enthusiastic proponent of the power of positive thinking and tireless self promotion, to heights of fame. The syntax idea gives experts in linguistics hope for lucrative employment opportunities. But most implementations of these hallowed “techniques” deliver massive computational overhead and outputs which require legions of expensive subject matter experts to keep on track.

The headline is one thing, but the write up is about another topic in my opinion. Here’s the passage I noted:

The basic problem with AI is no vendor is there yet.

Okay, maybe I did not correctly interpret “Semantic, Adaptive Search—Now That’s a Mouthful.” I just wasn’t expecting artificial intelligence, a very SEO type term.

But I was off base. The real subject of the write up seems to be captured in this passage:

I used to be organized, but somehow I lost that admirable trait. I blame it on information overload. Anyway, I now spend quite a bit of time searching for my blogs, white papers, and research, as I have no clue where I filed them. I have resorted to using multiple search criteria. Something I do, which is ridiculous, is repeat the same erroneous search request, because I know it’s there somewhere and the system must have misunderstood, right? So does the system learn from my mistakes, or learn the mistakes? Does anyone know?

Okay, disorganized. I would never have guessed without a title that references semantic and adaptive search, the lead paragraph about artificial intelligence, and this just cited bit of exposition which makes clear that the searcher cannot make the search systems divulge the needed information.

One factoid in the write up is that a searcher will use 2.73 terms per query. I think that number applies to desktop boat anchor searches from the Dark Ages of old school querying. Today, more than 55 percent of queries are from mobile devices. About 20 percent of those are voice based. Other queries just happen because a greater power like Google or Microsoft determines what you “really” wanted is just the ticket. To me, the shift from desktop to mobile makes the number of search terms in a query a tough number to calculate. How does one convert data automatically delivered to a Google Map when one is looking for a route with an old school query with 2.73 terms? Answer: You maybe just use whatever number pops out from a quick Bing or Google search from a laptop and go with the datum in a hit on an ad choked result list.

The confused state of search and content processing vendors is evident in their marketing, their reliance on jargon and mumbo jumbo, and fuzzy thinking about obtaining information to meet a specific information need.

I suppose there is hope. One can embrace a taxonomy and life will be good. On the other hand, disorganization does not bode well for a taxonomy created by a person who cannot locate information.

Well, one can use smart software to generate those terms, the Use Fors and the See Alsos. One can rely on massive amounts of Big Data to save the day. One can allow a busy user of SharePoint to assign terms to his or her content. Many good solutions which make information access a thrilling discipline.

Now where did I put that research for my latest book, “The Dark Web Notebook”? Ah, I know. In a folder called “DWNB Research” on my back up devices with hard copies in a banker’s box labeled “DWNB 2016-2017.”

Call me old fashioned but the semantic, syntactic, artificially intelligent razzmatazz underscores the triumph of jargon over systems and methods which deliver on point results in response to a query from a person who knows that for which he or she seeks.

Plus, I have some capable research librarians to keep me on track. Yep, real humans with MLS degrees, online research expertise, and honest-to-god reference desk experience.

Smart software and jargon requires more than disorganization and arm waving accompanied by toots from the jargon tuba.

Led by founder and CEO Falon Fatemi, Node emerged from stealth on Tuesday ready to take on its lofty goal of changing the way we discover information. By using AI to connect you or your business with the right opportunity at the right time, Node wants to ‘accelerate serendipity’ on the web. Node’s patent-pending technology works by indexing people, places, products, and companies instead of web pages, and using this data to connect customers to opportunities. So far, it has half a billion profiles. The AI understands the relationships between people and companies, and can marry its data layer with a customer’s personal data. Node is currently integrated with Salesforce, and customers can ask questions like ‘What company will be most interested in my product?’ Node will tell the customer who or what they need to connect with, why it came up with that answer, and even what to say to make the most of the opportunity. It’s searching without using a search box.

Node began as Fatemi’s personal project, and now her firm has raised $16.3 million in funding so far. She envisions her new tech as the “intelligence layer of the internet,” as Cakebread puts it, and believes any realm of life, from sales strategy to dating options, could benefit from this approach.

Fatemi started at Google while still in college. She wrote an article for Fast Company a couple years ago, “I Joined Google at 19. Here’s What I Learned,” in which she credits her time at Google with installing many of the qualities that have made her a successful entrepreneur. See that article for those lessons learned.

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Stephen E. Arnold monitors search, content processing, text mining
and related topics from his high-tech nerve center in rural Kentucky.
He tries to winnow the goose feathers from the giblets. He works with colleagues
worldwide to make this Web log useful to those who want to go
"beyond search". Contact him at sa [at] arnoldit.com. His Web site
with additional information about search is arnoldit.com.